code: def __init__(self, config: Dict[str, Any]) -> None:
      super().__init__()
  
      self.config = config
      self.cat_c_feat = config["fine_concat_coarse_feat"]
      self.W = self.config["fine_window_size"]
  
      d_model_c = self.config["coarse"]["d_model"]
      d_model_f = self.config["fine"]["d_model"]
      self.d_model_f = d_model_f
      if self.cat_c_feat:
          self.down_proj = nn.Linear(d_model_c, d_model_f, bias=True)
          self.merge_feat = nn.Linear(
              2 * d_model_f, d_model_f, bias=True
          )
  
      self._reset_parameters()
  
file_path: kornia/kornia/feature/loftr/loftr_module/fine_preprocess.py
imports: from typing import Any, Dict, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from kornia.core import Module, Tensor
label_desc: Use image node_id 1 to create a new FinePreprocess object from inherited base classes: Module with example: obj = FinePreprocess(config)